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X Demographics
Mendeley readers
Attention Score in Context
| Title |
RNA-Seq improves annotation of protein-coding genes in the cucumber genome
|
|---|---|
| Published in |
BMC Genomics, November 2011
|
| DOI | 10.1186/1471-2164-12-540 |
| Pubmed ID | |
| Authors |
Zhen Li, Zhonghua Zhang, Pengcheng Yan, Sanwen Huang, Zhangjun Fei, Kui Lin |
| Abstract |
As more and more genomes are sequenced, genome annotation becomes increasingly important in bridging the gap between sequence and biology. Gene prediction, which is at the center of genome annotation, usually integrates various resources to compute consensus gene structures. However, many newly sequenced genomes have limited resources for gene predictions. In an effort to create high-quality gene models of the cucumber genome (Cucumis sativus var. sativus), based on the EVidenceModeler gene prediction pipeline, we incorporated the massively parallel complementary DNA sequencing (RNA-Seq) reads of 10 cucumber tissues into EVidenceModeler. We applied the new pipeline to the reassembled cucumber genome and included a comparison between our predicted protein-coding gene sets and a published set. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 4 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 191 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 9 | 5% |
| Sweden | 3 | 2% |
| Italy | 2 | 1% |
| United Kingdom | 2 | 1% |
| Canada | 2 | 1% |
| India | 1 | <1% |
| Czechia | 1 | <1% |
| Brazil | 1 | <1% |
| Mexico | 1 | <1% |
| Other | 6 | 3% |
| Unknown | 163 | 85% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 57 | 30% |
| Student > Ph. D. Student | 48 | 25% |
| Student > Master | 22 | 12% |
| Student > Doctoral Student | 13 | 7% |
| Student > Bachelor | 11 | 6% |
| Other | 23 | 12% |
| Unknown | 17 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 129 | 68% |
| Biochemistry, Genetics and Molecular Biology | 32 | 17% |
| Computer Science | 4 | 2% |
| Social Sciences | 2 | 1% |
| Earth and Planetary Sciences | 2 | 1% |
| Other | 2 | 1% |
| Unknown | 20 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 May 2023.
All research outputs
#3,172,105
of 22,656,971 outputs
Outputs from BMC Genomics
#1,221
of 10,607 outputs
Outputs of similar age
#18,121
of 141,797 outputs
Outputs of similar age from BMC Genomics
#12
of 104 outputs
Altmetric has tracked 22,656,971 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,607 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 88% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 141,797 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 104 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.